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A two-level, discrete particle approach for large-scale simulation of colloidal aggregates

机译:二级,离散粒子方法用于胶体聚集体的大规模模拟

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Most numerical techniques employed for aggregation simulation are based on equilibrium growth assumption and Smoluchowski theory. We present a new two-level discrete particle model, which can be employed in simulating large colloidal clusters in highly nonequilibrium physical conditions. We consider the system of colloidal particles (CP) interacting via conservative CP-CP repulsive-attractive two-body forces, which is initially mixed in a dissipative solvent. In order to obtain a high-resolution picture of colloidal dynamics, we employ around 20 million particles consisting of two kinds of particles. For bridging the spatio-temporal scales between nanoscale colloidal and the solvent particles (SP), the solvent is modeled by dissipative particle dynamics (DPD) fluid. We focus on the systems size for which the CP-SP interactions can also be described by the DPD forces. Unlike previous numerical techniques, the two-level particle model can display much more realistic physics, thus allowing for the simulation of aggregation for various types of colloids and solvent liquids in a broad range of conditions. We show that not only large and static clusters but also the initial stages of aggregation evolution can be better scrutinized. The large-scale simulation results obtained in two-dimensions show that the mean cluster size grows with time t according to the power law t(K). Because of the time-dependence of growth mechanism, the value of kappa, necessarily must change. We have first kappa = 1 with a Value of 1 achieved asymptotically with time. We can also discern intermediate-scale structures. We emphasize that the method developed here can be easily extended to algorithms dealing with multi-level hierarchy and multiphase fluid dynamics. [References: 36]
机译:用于聚集模拟的大多数数值技术都是基于平衡增长假设和Smoluchowski理论。我们提出了一个新的两级离散粒子模型,该模型可用于在高度非平衡物理条件下模拟大型胶体簇。我们考虑通过保守的CP-CP排斥力吸引的两体力相互作用的胶体粒子(CP)系统,该力最初混合在耗散溶剂中。为了获得胶体动力学的高分辨率图片,我们使用了大约2000万个由两种粒子组成的粒子。为了弥合纳米级胶体和溶剂颗粒(SP)之间的时空尺度,通过耗散颗粒动力学(DPD)流体对溶剂进行建模。我们专注于CP-SP相互作用也可以由DPD力描述的系统规模。与以前的数值技术不同,两级粒子模型可以显示更为逼真的物理学,因此可以在各种条件下模拟各种类型的胶体和溶剂液体的聚集。我们显示,不仅大型和静态群集,而且聚合演化的初始阶段都可以得到更好的检查。在二维上获得的大规模仿真结果表明,平均簇大小根据幂律t(K)随着时间t增长。由于增长机制的时间依赖性,因此,κ值必定必须改变。我们的第一个kappa = 1,其值1随时间渐近达到。我们还可以辨别中等规模的结构。我们强调,这里开发的方法可以轻松扩展到处理多级层次结构和多相流体动力学的算法。 [参考:36]

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